Mixed-model analysis of the relationships between training loads and heart rate variability in elite swimmers - Hellard, P.; Cattaneo, S.; Houel, N.; Schmitt, L.; Barale, F.; Lacoste, L.; Rey, J. L. (Biomechanics and Medicine in Swimming X, 2006)
Heart rate variability (HRV) analysis is a well-recognized method to assess autonomic nervous System perturbations, and was shown to be influenced by the fitness and the fatigue in endurance athletes (6). The relationships between HRV and training loads were shown to be highly individualized (6), and dependent of several factors, including gender (G), training level (L) and specialty (S) (1). Indeed, the HRV responses could probably be influenced by long-term effects (LTE) (6). When only few repeated measurements are available for several subjects characterized by a large inter-individual variability, mixed models provide an attractive solution (2). Instead of constructing a personalized model for each subject, a model of common behavior is constructed, allowing parameters to vary from one individual to another, to take into account the heterogeneity between subjects. The aim of this study was to investigate the immediate and differed effects of training loads on HRV taking into account: (a) the mean structure of the covariates G, L, S; (b) individual profiles, and (c) subpopulation profiles.